Review on emerging research topics with key-route main path analysis
- 4 Downloads
The fast development of the emerging research topics field results in hundreds of theoretical and empirical publications. However, to our knowledge, there is no comprehensive and objective literature review on this field until now. To this end, a citation network consisting of 1607 papers between 1965 and early 2019 is explored to discover the knowledge diffusion trajectory of the emerging research topics field by the key-route main path analysis approach, armed with the traversal weight of search path link count. From the convergence–divergence patterns in the local and global main paths, the development of emerging research topics field can be divided into three different stages: the emergence, exploration and development stages. In the meanwhile, several research drifts can also be observed: (1) from citation-based approaches to machine learning based ones, (2) from the measurement to the identification, and (3) from the papers to the patents. Finally, the directions of future research are suggested.
KeywordsEmerging research topics Literature review Key-route main path analysis Knowledge diffusion trajectory
This work was supported partially by the Social Science Foundation of Beijing Municipality (Grant Number 17GLB074), and Natural Science Foundation of Guangdong Province (Grant Number 2018A030313695). Our gratitude also goes to the anonymous reviewers and the editor for their valuable comments.
- Batagelj, V. (2003). Efficient algorithms for citation network analysis. University of Ljubljana, Institute of Mathematics, Physics and Mechanics, Department of Theoretical Computer Science.Google Scholar
- Garner, J., Carley, S., Porter, A., & Newman, N. (2017). Technological emergence indicators using emergence scoring. In 2017 Portland international conference on management of engineering and technology (PICMET). Google Scholar
- Liu, J., & Lu, L. (2012). An integrated approach for main path analysis: Development of the Hirsch index as an example. Journal of the Association for Information Science and Technology,63(3), 528–542.Google Scholar
- Lu, C., Hou, H., Ding, Y., & Zhang, C. (2019). Review of international studies on discovering emerging topics. Journal of the China Society for Scientific and Technical Information,38(1), 97–110.Google Scholar
- Porter, A. L., Garner, J., Carley, S. F., & Newman, N. C. (2018). Emergence scoring to identify frontier R&D topics and key players. Technological Forecasting and Social Change, 146, 628–643.Google Scholar
- Reiss, T., Vignola-Gagné, E., Kukk, P., Glänzel, W., & Thijs, B. (2013). ERACEP – Emerging Research Areas and their Coverage by ERC-supported Projects. Technical Report European Research Council. Google Scholar
- Xu, S., Hao, L., An, X., Yang, G., & Wang, F. (2019). Emerging research topics detection with multiple machine learning models. Journal of Informetrics (accepted).Google Scholar